جست‌وجوی استاد و پژوهشگر

David B. Lindellمشاهده پروفایل

استادیار

• Computational Imaging
• Computer Vision
• Non-Line-of-Sight Imaging
• +۵ مورد دیگر

David B. Lindell is an Assistant Professor in the Department of Computer Science at the University of Toronto, with affiliations to the Vector Institute and AXL. He is a founding member of the Toronto Computational Imaging Group. His research focuses on physically based intelligent sensing, integrating physical models, signal processing, and AI to advance sensing systems. Notable projects include imaging around corners, through scattering media, and developing machine learning algorithms for 3D scene reconstruction. Education: Ph.D. in Computational Imaging from Stanford University (advisor: Gordon Wetzstein). Awards include the 2024 Ontario Early Researcher Award and the Best Student Paper at CVPR 2025. His work combines computational imaging with applications in computer graphics and autonomous systems. Research interests span non-line-of-sight imaging, single-photon sensing, and neural representations. Key contributions include the Light-Cone Transform (Nature 2018), confocal diffuse tomography (Nature Communications 2020), and AutoInt (CVPR 2021). His lab develops systems for 3D reconstruction, transient imaging, and photon-efficient sensors. Selected grants and support: NSF CAREER Award, DARPA REVEAL program, and KAUST Visual Computing Center funding. Active collaborations with industry and academic institutions on autonomous driving and medical imaging applications.

Mark Crowleyمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Deep Learning
• Manifold Learning
• +۱۲ مورد دیگر

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, with a cross-appointment in the Cheriton School of Computer Science. He is a member of the Waterloo Artificial Intelligence Institute (WAII) and the Waterloo Institute for Complexity and Innovation (WICI), and serves as National Secretary of the Canadian Artificial Intelligence Association (CAIAC). His educational background includes a Ph.D. and M.Sc. in Computer Science from the University of British Columbia, where he worked in the Laboratory for Computational Intelligence, and a B.A. in Computer Science from York University. He completed a postdoctoral fellowship at Oregon State University working with Tom Dietterich's machine learning group. Crowley's research focuses on developing dependable and transparent algorithms to augment human decision-making in complex domains with multiple agents, spatial structure, or uncertainty. His work spans Reinforcement Learning , Deep Learning , Ensemble Methods , and Manifold Learning . He frequently collaborates with researchers in applied fields including Computational Sustainability, Sustainable Forest Management, Autonomous Driving, Medical Imaging, and Material Design. His research is motivated by both theoretical opportunities and real-world challenges such as forest fire management, automotive applications, and medical imaging. His recent publications demonstrate a strong focus on addressing challenges in reinforcement learning, particularly around observation costs, multi-agent systems, and causal representation learning. His work on ChemGymRL provides a significant contribution to digital chemistry and material design through reinforcement learning frameworks. The textbook Elements of Dimensionality Reduction and Manifold Learning represents a major contribution to the theoretical foundations of machine learning. Crowley actively supervises graduate students, with recent thesis completions including Shayan Shirahmadi Gale Bagi (PhD, Feb 2025) and Oleksandra Nahorna (MASc, Dec 2024). His lab, UWECEML (Waterloo ECE Machine Learning Lab), focuses on developing new algorithms at the intersection of Machine Learning, Optimization, and Probabilistic Modeling. He teaches courses including ECE 457C (Reinforcement Learning), ECE 657A (Data & Knowledge Modelling & Analysis), and ECE 457B (Fundamentals of Computational Intelligence). His blog Computationally Thinking explores AI, machine learning, and the societal impact of these technologies.

• Family Dynamics and Health
• Health Inequalities
• Life Course Approach
• +۳ مورد دیگر

Professor Lisa Strohschein holds dual roles as a Professor in the Sociology Department and Director of Undergraduate Programs at the University of Alberta's Faculty of Arts. Her research focuses on family dynamics and health inequalities, employing longitudinal methodologies to analyze large datasets. She teaches courses on health sociology, mental illness, and socialization, emphasizing sociological perspectives on health distribution and care systems. Her research interests include the interplay between socioeconomic factors and mental health, gender disparities in marital outcomes, and generational shifts in parenting practices. She has published extensively on topics like teen pregnancy correlates, poverty dynamics, and the mental health implications of family structures. Strohschein has received the 2019-20 Killam Annual Professorship and serves as Editor-in-Chief of Canadian Studies in Population, a peer-reviewed journal focusing on demographic research. She also contributes to policy through roles like membership in Statistics Canada's Demographic Statistics Advisory Committee and past presidency of the Canadian Population Society. Her scholarly work bridges theoretical frameworks (life course, stress process theory) with methodological rigor, often using growth curve models and competing risks analysis. Current research trends emphasize cross-national comparisons and applied policy relevance, particularly in understanding how family transitions impact health across the life course.

Kimon Fountoulakisمشاهده پروفایل

دانشیار

• Machine Learning on Graphs
• Numerical Optimization
• Graph Algorithms
• +۲ مورد دیگر

Kimon Fountoulakis is an Associate Professor at the University of Waterloo. His research focuses on Machine Learning on Graphs and Numerical Optimization, with a strong emphasis on algorithmic methods for graph-structured data. He holds a Ph.D. from The University of Edinburgh (2015), an M.Sc. from The University of Edinburgh (2010), and a B.Sc. from Athens University of Economics and Business (2009). His work spans theoretical foundations and practical applications in graph algorithms, optimization, and machine learning. Research interests include graph neural networks, local graph clustering algorithms, and algorithmic reasoning. His contributions address challenges in graph representation learning, message-passing architectures, and scalable optimization methods. Notable themes in his publications include improving counting abilities of vision-language models, analyzing graph convolutions, and developing flow-based clustering techniques with statistical guarantees. His work often bridges theory and practice, with applications in network analysis, pandemic containment strategies, and high-performance computing. While no specific grants or awards are listed, his research demonstrates significant contributions to graph-based machine learning and optimization. He maintains a research group at the University of Waterloo, with a focus on developing open-source tools and frameworks for graph algorithms. His lab’s work emphasizes local graph clustering methods and their scalability in real-world networks.

Jino Distasioمشاهده پروفایل

استاد

• Urban Geography
• Cultural Geography
• Social Geography
• +۵ مورد دیگر

Jino Distasio is a Professor and Acting Dean of Science at The University of Winnipeg, Department of Geography. He teaches Urban Geography, Cultural Geography, and Social Geography, with courses like GEOG-3413 Urban Revitalization and GEOG-3430 Housing and Neighbourhood Planning . His research focuses on housing and neighborhood development, city planning, urban revitalization, homelessness, mental health, and urban transportation. Teaching Areas : Urban Geography, Cultural Geography, Social Geography Key Collaborations : Institute of Urban Studies (U. of Winnipeg), Housing First initiatives, interdisciplinary teams in public health and social policy His recent publications highlight Housing First interventions, urban policy impacts on homelessness, and social determinants of health. Scientific awards and honors were not explicitly mentioned in the provided text.

• Databases
• Data Mining
• Machine Learning
• +۳ مورد دیگر

Ming-Syan Chen is a distinguished academic holding dual roles as a Distinguished Research Fellow and Director of the Research Center for Information Technology Innovation (CITI) at Academia Sinica, Taiwan, and a Distinguished Professor jointly appointed across multiple departments at National Taiwan University (NTU), including Electrical Engineering (EE), Computer Science and Information Engineering (CSIE), and the Graduate Institute of Communication Engineering (GICE). His career spans academia and industry, with prior roles as a research staff member at IBM Watson Research Center and leadership positions in Taiwan's technology sector. Education: He earned a B.S. in Electrical Engineering from National Taiwan University, followed by M.S. and Ph.D. degrees in Computer, Information, and Control Engineering from the University of Michigan, Ann Arbor. Research Interests: Chen's work focuses on databases, data mining, machine learning, multimedia networking, and cloud computing. He has authored over 350 papers and holds numerous patents, contributing to foundational advancements in query processing, data management, and networked systems. Award Highlights: Recipient of ACM and IEEE Fellowships, National Chair Professorship (lifetime honor), Teco Award, Pan Wen Yuan Distinguished Research Award, and IBM's Outstanding Innovation Award. His contributions span research, teaching, and technology commercialization. Leadership & Service: Former Dean of NTU's College of Electrical Engineering and Computer Science, CEO of Taiwan's Networked Communication Program, and Editor-in-Chief of the International Journal of Electrical Engineering. He has chaired international conferences and served on editorial boards of journals like IEEE TKDE and VLDB. Labs & Teams: Leads the Network Database Laboratory and collaborates on national initiatives in information and communication technologies. His research groups focus on data science, distributed systems, and social network analysis.

• Suicide
• Metascience
• Emotion
• +۴ مورد دیگر

Elisha David Klonsky is a Professor in the Department of Psychology at the University of British Columbia, Faculty of Arts. His primary research classification is Clinical Psychology with a secondary focus in Social/Personality Psychology. He directs the Personality, Emotion, and Behaviour Lab (PEBLab) and maintains an active research program while accepting graduate students for the 2023/24 application cycle. Dr. Klonsky earned his PhD from the University of Virginia in 2005. His educational background has positioned him as a leading researcher in clinical psychology, particularly in suicide research. Dr. Klonsky's research interests center on suicide theory, motivations, and the transition from suicidal thoughts to attempts. His work also spans metascience, emotion research, and psychological/clinical assessment. He has developed the influential Three-Step Theory (3ST) of suicide, which operates within an ideation-to-action framework. His research examines how emotional pain, impulsivity, and nonsuicidal self-injury relate to suicidal behavior, with particular interest in developing better assessment tools for clinical practice. Recent work has expanded into metascience, addressing the replication crisis in psychology. His publication record shows consistent high-impact work primarily in suicide research, with recent emphasis on suicide motivations, emotion measurement, and theoretical frameworks. The research demonstrates strong clinical applicability while maintaining rigorous scientific methodology. Dr. Klonsky has received numerous prestigious awards including: UBC Killam Research Prize (2020) Killam Faculty Research Fellowship (2017) American Association of Suicidology: Edwin S. Shneidman Award (2015) Association for Psychological Science Rising Star (2011) David Shakow Early Career Award (2011) American Psychological Association Fellow (2010) Dr. Klonsky has successfully mentored numerous graduate students who have gone on to academic positions at institutions including Old Dominion University, McGill University, Wesleyan University, and Texas Tech University. His research has been supported by significant funding from organizations including the Social Sciences and Humanities Research Council, American Foundation for Suicide Prevention, and National Institute of Mental Health. Current projects include studies on suicidality in youth with autism spectrum disorder and advancing the measurement of emotional experience. The Personality, Emotion, and Behaviour Lab maintains active research programs in suicide, emotion, metascience, and related areas, with particular emphasis on developing parsimonious models of suicide and better understanding suicide motivations and warning signs.

Freda Shiمشاهده پروفایل

استادیار

• computational linguistics
• natural language processing
• computational multilingualism
• +۵ مورد دیگر

Freda Shi is an Assistant Professor at the David R. Cheriton School of Computer Science at the University of Waterloo and a Faculty Member at the Vector Institute, where she holds a Canada CIFAR AI Chair. She joined the University of Waterloo in July 2024 after completing her Ph.D. at the Toyota Technological Institute at Chicago. Educational Background: Ph.D. in Computer Science, Toyota Technological Institute at Chicago (2024), advised by Professors Karen Livescu and Kevin Gimpel Bachelor's degree in Intelligence Science and Technology (Computer Science Track) with a minor in Sociology, Peking University (2018) Dr. Shi's research focuses on computational linguistics and natural language processing, particularly on deeper understandings of natural language and the human language processing mechanism. She is especially interested in learning language through grounding, computational multilingualism, and related machine learning aspects. Her work aims to inform the design of more efficient, effective, safe, and trustworthy NLP systems. She leads the CompLING Lab at the University of Waterloo, which investigates how language models process spatial relationships and acquire linguistic structures through grounded experiences. Her publication record shows a consistent trajectory of high-impact research, with recent work focusing on spatial reasoning in vision-language models, multilingual chain-of-thought capabilities, and grounded language acquisition. She has published in top-tier conferences including ACL, EMNLP, ICLR, and NAACL, with several papers receiving notable recognition including Best Paper Nominee status at multiple venues. Her research bridges theoretical linguistics with practical NLP applications, demonstrating how linguistic insights can improve AI systems. Scientific Recognition: Canada CIFAR AI Chair (2024) Google Ph.D. Fellowship Thesis of Distinction for her doctoral work Multiple Best Paper Nominee awards at major NLP conferences Dr. Shi teaches CS 784: Computational Linguistics and CS 486/686: Introduction to Artificial Intelligence at the University of Waterloo. She actively contributes to the NLP research community through conference participation, program committee service, and collaborative projects. Her research has significant implications for creating more robust, human-like language understanding systems and advancing the field of grounded language learning in artificial intelligence.

Adam Kingمشاهده پروفایل

استادیار

• Labour and employment regulation
• Employment standards enforcement
• Indigenous labour relations
• +۲ مورد دیگر

Adam King is an Assistant Professor in the Labour Studies Program at the Faculty of Arts, University of Manitoba. His research focuses on labor regulation, employment standards enforcement, Indigenous labor dynamics, deindustrialization impacts, and labor market policy. He co-investigates a SSHRC Partnership Grant project on migrant labor in settler-colonial contexts. Education: PhD in Sociology (York University, 2019) MA in History (University of Toronto, 2011) BA in Sociology/History (Trent University, 2010) His research examines the political economy of labor regulation, including enforcement mechanisms in federally regulated sectors and contested Indigenous labor relations. He analyzes deindustrialization's social consequences and contributes to debates on job guarantee proposals and right-wing populism's influence on labor movements. Recent publications explore topics like Indigenous labor law frameworks, precarious creative workers' unionization, and gendered identities in deindustrializing communities. He actively engages with media outlets such as CBC, The Globe and Mail, and The Maple's 'Class Struggle' newsletter.

• Cultural Studies
• Globalization and Culture
• Entrepreneurship
• +۳ مورد دیگر

Tina Dacin is a Professor of Strategy and Organizational Behavior at the Smith School of Business, Queen's University, Canada. She holds the Stephen J.R. Smith Chair and serves as Director of the Community Impact Research Program. Her roles include former Director of the Smith School’s Centre for Social Impact, former University Senate member, and former Chair of the Principal’s Innovation Fund Committee. She co-founded the Community of Social Innovation Chair and holds affiliations with the Academy of Management and Informs. Education: Ph.D. (1993) in Business Administration from the University of Toronto and M.A. in Psychology from the University of New Brunswick. Research focuses on cultural heritage, social innovation/entrepreneurship, strategic alliances, and globalization. Key themes include custodianship, tradition preservation, place-making, and institutional dynamics. Recent work explores craft-based ventures, place-sensitive organizational practices, and institutional renewal in crises like the Detroit water wars. Awards: None explicitly listed, though her chair position reflects academic distinction. Teaching includes courses on global social impact and analytics/ethics policy. Labs/Teams: Leadership in the Community Impact Research Program and the Scotiabank Centre for Customer Analytics.

André Gagnéمشاهده پروفایل

استاد

• Christian Political Thought
• Global Pentecostal and Charismatic movements
• Reception of the Bible

André Gagné is a Full Professor and Chair of the Department of Theological Studies at Concordia University, currently on research leave (July-December 2025). His work bridges theology, political science, and sociology with global recognition through 400+ media features in outlets like The New York Times, The Guardian, and Le Monde. Education: Conjoint PhD from Université catholique de Louvain and Université de Montréal M.A. from Université de Montréal B.Th. from Université de Montréal His research centers on Christian Political Thought (examining theology-state dynamics), Global Pentecostal and Charismatic movements (analyzing their sociopolitical impact worldwide), and Reception History of the Bible (tracing interpretive trajectories across cultures). This interdisciplinary approach integrates historical analysis with contemporary case studies, particularly focusing on evangelical movements in the Americas and Europe. His eight books and recent journal articles reveal consistent thematic focus: the weaponization of spiritual warfare rhetoric in politics, apocalyptic narratives in populist movements, and religious violence in Western traditions. The 2024 publications on Trump-era evangelicalism demonstrate methodological innovation through media discourse analysis combined with theological critique. Scientific awards: Newsmaker of the Week (4 times) Newsmaker of the Month (4 times) President's Opinion Leader of the Year (2016) Expert Communicator of the Year (2024) Dr. Gagné supervises MA students in Theological Studies and PhD candidates in Individualized Programs and Humanities. His policy impact is evidenced by service on Public Safety Canada's National Expert Committee on Countering Radicalization to Violence (2023-2025), where he contributed theological perspectives on religious extremism. His media engagement strategy represents a deliberate effort to translate academic research for public discourse. He co-directs the Spirit, State, and Society podcast and maintains affiliations with Concordia's Centre for the Study of Learning and Performance, Université de Sherbrooke's Centre de recherche Société, Droit et Religions, and the multi-university Political Theology Research Group (McGill, Concordia, UdeM, ULaval).

Daniel Duttonمشاهده پروفایل

دانشیار

• Social Epidemiology
• Public Health Policy
• Health Economics
• +۳ مورد دیگر

Dr. Daniel Dutton is an Associate Professor in the Department of Community Health and Epidemiology at Dalhousie University's Faculty of Medicine, based at the Dalhousie Medicine New Brunswick campus in Saint John. His research focuses on how social environments influence health outcomes and the role of government policies in mitigating these impacts, particularly in areas like poverty, homelessness, and health economics. He holds adjunct roles at the University of New Brunswick (Sociology) and is the Scientific Director of APPTA, a hub bridging aging research and policy. He teaches courses in epidemiology, population health, and statistics. Education: PhD in Community Health Sciences (University of Calgary) MA in Economics (University of Calgary) BA Honours in Economics (Queen’s University) Research Interests: Dr. Dutton examines population-level health determinants, government policy effectiveness, and socioeconomic disparities. His work employs large datasets and econometric models to analyze topics such as homelessness incidence, healthcare cost savings through preventive measures, and the distributional impacts of public spending. Key Contributions: Scientific Director of the APPTA aging and technology hub. Co-founder of the IMPART research collaborative. Author of influential studies on Housing First programs, opioid prescribing patterns, and the fiscal benefits of guaranteed annual income policies. Advising & Grants: Supervises multiple MSc students and has collaborated on grants analyzing healthcare utilization in New Brunswick and Alberta. His work often intersects with policy-making, emphasizing actionable insights from quantitative research. Labs & Teams: Leads the Dutton Research Group, which uses mascot Odin the Saint Bernard to foster team cohesion. Active in interdisciplinary collaborations across public health, sociology, and economics.

Hiren Patelمشاهده پروفایل

استاد

• Real-Time Embedded Systems
• Computer Architecture
• Hardware for Machine Learning/AI
• +۹ مورد دیگر

Dr. Hiren Patel is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a Doctorate in Computer Engineering from Virginia Tech and previously worked as a postdoctoral fellow at UC Berkeley under Edward A. Lee. His research focuses on real-time embedded systems, computer architecture, machine learning hardware, and cybersecurity. He teaches courses like ECE 150 (Programming), ECE 320/429 (Computer Architecture), and ECE 327 (Digital Systems). Research Interests: Cyber-physical systems and hybrid architectures Hardware/software co-design methodologies Predictable cache coherence protocols IoT and edge computing systems Security in embedded and real-time systems Recent work emphasizes cache coherence solutions for safety-critical systems and GPU acceleration strategies. His publications address challenges in multicore predictability, FPGA bandwidth optimization, and autonomous robotics orchestration. No specific awards are listed, though his extensive publication record indicates significant contributions to embedded systems research. He currently oversees graduate student applications focusing on his core research areas.

Euijin Chooمشاهده پروفایل

استادیار

• Data-driven Cybersecurity
• Big Data Analytics
• Graph Mining
• +۶ مورد دیگر

Dr. Euijin (Alley) Choo is an Assistant Professor in the Department of Computer Science at the University of Alberta, specializing in data-driven cybersecurity and big data analytics. Her research focuses on AI-based cybersecurity solutions, anomaly detection in network traffic, and adversarial attacks on federated learning systems. She holds a Ph.D. from North Carolina State University and has held roles at Qatar Computing Research Institute, Korea University, and the University of Missouri-Rolla. Education: Ph.D., Computer Science, North Carolina State University (2015) M.S., Computer Science & Engineering, Korea University (2008) B.S. Dual Degree in Computer Science & Mathematics, Korea University (2006) Research Interests: Security and big data analysis intersections Federated learning security and privacy Anomaly detection in network logs and enterprise systems Malware/phishing detection using graph inference AI-driven threat intelligence aggregation Recent Grants: Mitacs Accelerate Program Grant: Fraud Detection in Financial Graphs ($60,000, 2025) National CyberSecurity Consortium Grant: IntruderInsight ($2M, 2025-2027) NSERC Discovery Grant: Threat Detection Framework ($180,000, 2025-2031) Awards: Best Paper Award at DBSEC 2015 NSERC Early Career Researcher Award (2025) Provost Fellowship (NC State, 2009-2010) Labs/Teams: Leads the Data-driven Network and Cyber Security (DANS) Lab, focusing on federated learning defenses, compromised entity detection, and malicious domain analysis.

Jane Gairمشاهده پروفایل

استاد آموزشی

• Medical Education
• Medical Genetics
• Science Outreach
• +۱ مورد دیگر

Dr. Jane Gair is a tenured Teaching Professor in the Division of Medical Sciences at the University of Victoria, where she teaches first and second-year medical students in the Island Medical Program (IMP). She serves as IMP Site Lead for Case-Based Learning (CBL) and Director for CBL Faculty Development, leading provincial curriculum implementation and faculty training. Her academic credentials include: BSc from McMaster University BSc from University of British Columbia (UBC) PhD from University of British Columbia (UBC) Her research centers on medical education methodologies including Problem-Based Learning (PBL) and Case-Based Learning (CBL), with emphasis on small-group pedagogy effectiveness. She maintains active scholarship in medical genetics and personalized medicine, as demonstrated through public lectures on epigenetics and genetic testing. International collaborations extend her work to the University of Newcastle (Australia), Patan Academy of Health Sciences (Nepal), and National University of Defense Technology (China). Dr. Gair directs UVic's branch of the national Let's Talk Science Outreach Program, engaging medical students in K-12 STEM education across Vancouver Island. This initiative serves as a core component of the FLEX course curriculum where she mentors students as Advisor, Assessor, and Supervisor. Her provincial faculty development work indicates ongoing grant-supported activities though specific funding sources aren't detailed. She maintains affiliations with the Centre for Biomedical Research (CBR) at UVic and the Centre for Health Education Scholarship (CHES) at UBC. Her leadership in Let's Talk Science coordinates medical student volunteers and community partners in delivering science literacy programs, with recent activities including 2023-2024 Mini Med School sessions on AI in healthcare, diabetes management, and genetic testing.